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  1. 防災科研関係論文

Automated extraction of inundated areas from multi-temporal dual-polarization radarsat-2 images of the 2011 central Thailand flood

https://nied-repo.bosai.go.jp/records/5782
https://nied-repo.bosai.go.jp/records/5782
5726acec-50e7-400d-aec6-d9623a8a9566
Item type researchmap(1)
公開日 2023-03-30
タイトル
言語 en
タイトル Automated extraction of inundated areas from multi-temporal dual-polarization radarsat-2 images of the 2011 central Thailand flood
言語
言語 eng
著者 Pisut Nakmuenwai

× Pisut Nakmuenwai

en Pisut Nakmuenwai

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Fumio Yamazaki

× Fumio Yamazaki

en Fumio Yamazaki

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Wen Liu

× Wen Liu

en Wen Liu

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抄録
内容記述タイプ Other
内容記述 c 2017, by the authors; licensee MDPI, Basel, Switzerland. This study examines a novel extraction method for SAR imagery data of widespread flooding, particularly in the Chao Phraya river basin of central Thailand, where flooding occurs almost every year. Because the 2011 flood was among the largest events and of a long duration, a large number of satellites observed it, and imagery data are available. At that time, RADARSAT-2 data were mainly used to extract the affected areas by the Thai government, whereas ThaiChote-1 imagery data were also used as optical supporting data. In this study, the same data were also employed in a somewhat different and more detailed manner. Multi-temporal dual-polarized RADARSAT-2 images were used to classify water areas using a clustering-based thresholding technique, neighboring valley-emphasis, to establish an automated extraction system. The novel technique has been proposed to improve classification speed and efficiency. This technique selects specific water references throughout the study area to estimate local threshold values and then averages them by an area weight to obtain the threshold value for the entire area. The extracted results were validated using high-resolution optical images from the GeoEye-1 and ThaiChote-1 satellites and water elevation data from gaging stations.
言語 en
書誌情報 en : Remote Sensing

巻 9, 号 1, 発行日 2017
出版者
言語 en
出版者 MDPI AG
ISSN
収録物識別子タイプ EISSN
収録物識別子 2072-4292
DOI
関連識別子 10.3390/rs9010078
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